{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3cd172d3",
   "metadata": {},
   "outputs": [],
   "source": [
    "\"\"\"\n",
    "Created on Mon May 16 19:00:32 2022\n",
    "@author: Ajit Johnson Nirmal\n",
    "SCIMAP tutorial May 2022\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7a1c1cc4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# load packages\n",
    "import scimap as sm\n",
    "import scanpy as sc\n",
    "import pandas as pd\n",
    "import anndata as ad"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e2f30407",
   "metadata": {},
   "outputs": [],
   "source": [
    "common_path = \"/Users/aj/Dropbox (Partners HealthCare)/conferences/scimap_tutorial/may_2022_tutorial/\"\n",
    "#common_path = \"C:/Users/ajn16/Dropbox (Partners HealthCare)/conferences/scimap_tutorial/may_2022_tutorial/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ecd0fb93",
   "metadata": {},
   "outputs": [],
   "source": [
    "# load data\n",
    "#adata = sm.pp.mcmicro_to_scimap (image_path= str(common_path) + 'exemplar_001/quantification/unmicst-exemplar-001_cell.csv')\n",
    "#manual_gate = pd.read_csv(str(common_path) + 'manual_gates.csv')\n",
    "#adata = sm.pp.rescale (adata, gate=manual_gate)\n",
    "#phenotype = pd.read_csv(str(common_path) + 'phenotype_workflow.csv')\n",
    "#adata = sm.tl.phenotype_cells (adata, phenotype=phenotype, label=\"phenotype\") \n",
    "# add user defined ROI's before proceeding"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "360428e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# load saved anndata object\n",
    "adata = ad.read(str(common_path) + 'may2022_tutorial.h5ad')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "59758fee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 11170 × 9\n",
       "    obs: 'X_centroid', 'Y_centroid', 'Area', 'MajorAxisLength', 'MinorAxisLength', 'Eccentricity', 'Solidity', 'Extent', 'Orientation', 'imageid', 'phenotype', 'index_info', 'ROI', 'ROI_individual'\n",
       "    uns: 'all_markers', 'dendrogram_phenotype'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adata"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad48620c",
   "metadata": {},
   "source": [
    "### Investigate cell-type composition within the ROI's"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5c8ca0f8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# https://scimap.xyz/All%20Functions/C.%20Plotting/sm.pl.stacked_barplot/\n",
    "sm.pl.stacked_barplot (adata,\n",
    "                       x_axis='ROI_individual',\n",
    "                       y_axis='phenotype',\n",
    "                       method='absolute')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "0404b8ba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the number of cells normalized to 100% \n",
    "sm.pl.stacked_barplot (adata,\n",
    "                       x_axis='ROI_individual',\n",
    "                       y_axis='phenotype',\n",
    "                       method='percent')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "00776b3e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# specify the elements to be in the plot\n",
    "x_axis_elements = ['CD57-low-1', 'CD57-low-2', 'CD57-low-3', 'CD57-high-2', 'CD57-high-1', 'CD57-high-3']\n",
    "y_axis_elements = ['ASMA+ cells', 'Myeloid', 'NK cells', 'Neutrophils', 'Other Immune cells', 'Treg', 'Tumor']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "28dfe1a7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# replot\n",
    "sm.pl.stacked_barplot (adata,\n",
    "                       x_axis='ROI_individual',\n",
    "                       y_axis='phenotype',\n",
    "                       method='percent',\n",
    "                       subset_xaxis=x_axis_elements,\n",
    "                       subset_yaxis=y_axis_elements)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "68337884",
   "metadata": {},
   "outputs": [],
   "source": [
    "# quiet a number of parameters to play around:\n",
    "sm.pl.stacked_barplot (adata, \n",
    "                x_axis='ROI_individual', y_axis='phenotype', \n",
    "                subset_xaxis=x_axis_elements, subset_yaxis=y_axis_elements, \n",
    "                order_xaxis=None, order_yaxis=None, \n",
    "                method='percent', plot_tool='plotly', \n",
    "                matplotlib_cmap=None, \n",
    "                matplotlib_bbox_to_anchor=(1, 1.02), \n",
    "                matplotlib_legend_loc=2, \n",
    "                return_data=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3430ccd2",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "b4a9013f",
   "metadata": {},
   "source": [
    "### Calculate the fold change in cell types between the different ROI's"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "ebca1965",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/envs/scimap/lib/python3.9/site-packages/scimap/tools/_foldchange.py:102: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "/opt/anaconda3/envs/scimap/lib/python3.9/site-packages/scimap/tools/_foldchange.py:103: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "/opt/anaconda3/envs/scimap/lib/python3.9/site-packages/scimap/tools/_foldchange.py:104: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "/opt/anaconda3/envs/scimap/lib/python3.9/site-packages/scimap/tools/_foldchange.py:109: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n",
      "/opt/anaconda3/envs/scimap/lib/python3.9/site-packages/scimap/tools/_foldchange.py:110: SettingWithCopyWarning:\n",
      "\n",
      "\n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "calculating P values\n"
     ]
    }
   ],
   "source": [
    "adata = sm.tl.foldchange (adata, \n",
    "                          from_group=['CD57-low-1', 'CD57-low-2', 'CD57-low-3'], \n",
    "                          to_group=None, \n",
    "                          imageid='ROI_individual', \n",
    "                          phenotype='phenotype',\n",
    "                          normalize=True, \n",
    "                          subset_phenotype=None, \n",
    "                          label='foldchange')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b01dc2bc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AnnData object with n_obs × n_vars = 11170 × 9\n",
       "    obs: 'X_centroid', 'Y_centroid', 'Area', 'MajorAxisLength', 'MinorAxisLength', 'Eccentricity', 'Solidity', 'Extent', 'Orientation', 'imageid', 'phenotype', 'index_info', 'ROI', 'ROI_individual'\n",
       "    uns: 'all_markers', 'dendrogram_phenotype', 'foldchange_pval', 'foldchange_fc'"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ecef1c39",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Heatmap of foldchnage  \n",
    "sm.pl.foldchange (adata, label='foldchange', method='heatmap',\n",
    "                     p_val=0.05, nonsig_color='grey',\n",
    "                     cmap = 'vlag', log=True, center=0, linecolor='black',linewidths=0.7,\n",
    "                     vmin=-5, vmax=5, row_cluster=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "0c0d912f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Parallel_coordinates plot of the foldchanges\n",
    "sm.pl.foldchange (adata, label='foldchange', \n",
    "                  subset_xaxis = ['ASMA+ cells', 'NK cells', 'Neutrophils', 'Treg', 'Tumor'],\n",
    "                log=True, method='parallel_coordinates', invert_axis=True,\n",
    "                parallel_coordinates_color=['black','blue','green','red','#000000'],\n",
    "                matplotlib_bbox_to_anchor=(1.04,1),\n",
    "                matplotlib_legend_loc='upper left',\n",
    "                xticks_rotation=90,\n",
    "                return_data = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "7d29c09d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# save adata\n",
    "adata.write(str(common_path) + 'may2022_tutorial.h5ad')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3d31da49",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
